This study gives examples for implementing technology-facilitated approaches and provides the following recommendations for conducting such longitudinal, sensor-based research, with both environmental and wearable sensors in a health care setting: pilot test sensors and software early and often; build trust with key stakeholders and with potential participants who may be wary of sensor-based data collection and concerned about privacy; generate excitement for novel, new technology during recruitment; monitor incoming sensor data to troubleshoot sensor issues; and consider the logistical constraints of sensor-based research.
L’Hommedieu M, L’Hommedieu J, Begay C, Schenone A, Dimitropoulou L, Margolin G, Falk T, Ferrara E, Lerman K, Narayanan S. (2019). Lessons Learned: Recommendations For Implementing a Longitudinal Study Using Wearable and Environmental Sensors in a Health Care Organization. JMIR Mhealth Uhealth, 7(12):e13305.
We’re going to be seeing more and more of this type of research in healthcare organisations, which I think is a good thing, given the following caveats (I’m sure that there are many more):
- We still need to be critical about how sensors record data, what kind of data they record, and what kinds of questions are prioritised with this type of research.
- Knowing more about how bodies work at the physiological level doesn’t say anything about the social, political, ethical, etc. factors that are responsible for the bigger health issues of our time e.g. chronic diseases of life.
- Behaviour can be tracked but the underlying beliefs that drive behaviour are still opaque. We need to be careful not to confuse behaviour with reasons for that behaviour.
Using sensors for data collection allows us to overcome the limitations of traditional data collection tools, such as surveys, as sensor data are considered to be more objective and accurate.
The reason I think that sensor-based research is, in general, a good thing is because the questions that you’re likely to ask in these kinds of studies are the same questions that we currently use observation and participant self-report to answer. We know that these forms of data collection are inherently unreliable so it’s interesting to see people trying to address this.
However, even assuming that sensor-based studies are more reliable (and we would first need to ask, reliable against what outcomes?), having more reliable data says little about whether the questions and corresponding data are valid. In other words, we need to be careful that that date being collected is appropriate for answering the types questions we’re asking.
Finally, it stands to reason that once we have the data on the behaviour (the easy part) we still need to do the hard research that gets at the underlying reasons for why people behave in the way that they do. Simply knowing that people tend to do X is only the first step. Understanding why they do X and not Y is another step (possibly determined by interviews for FGDs), and then presumably trying to get them to change their behaviour may be the hardest part of all.